977 resultados para Supply network mapping


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This paper proposes a model to explain the differences between outcomes of referenda and the voting trends suggested by polls. Two main effects are at stake. First, the evolution of the voters' attitudes is conditional on the public information made available to them. Second, the predisposition toward abstention among individuals within each voting group may be different. Our model describes how these two aspects of decision making may interact, showing how publicly available information may amplify the distinct tendency toward abstention between both groups and thus affect the outcome of the referendum.

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I relate hours worked with taxes on consumption and labor. I propose a model and compare its predictions for Portugal, France, Spain, United Kingdom and United States. Hours per worker in Portugal decreased from 35.1 in 1986 to 32.6 in 2001. With only the parameters and the taxes for Portugal, the model predicts the hours worked in 2001 with an error of only 12 minutes from the actual hours. Across countries, most predictions differ from the data by one hour or less. The model is able to explain the trend in hours with only the changes in taxes.

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I relate hours worked with taxes on consumption and labor for Portugal, France, Spain, United Kingdom and United States. From 1986 to 2001, hours per worker in Portugal decreased from 35.1 to 32.6. With the parameters for Portugal, the model predicts hours worked in 2001 with an error of only 12 minutes from the actual hours. Across countries, most predictions differ from the data by one hour or less. The model is not sensible to special assumptions on the parameters. I calculate the long run effects of taxes on consumption, hours, capital and welfare for Portugal. I extend the model to discuss implications for Social Security. I discuss the steady state and the transition from a pay-as-you-go to a fully funded system.

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This article focuses on the different images of Mediterranean Portugal developed by three important Portuguese social scientists of the 20th century: the geographer Orlando Ribeiro, the ethnologist Jorge Dias and the social anthropologist José Cutileiro. The article argues that these different images stem from different ideological attitudes towards the countryside, ranging from pastoral to counter-pastoral, and are also related to different ways of addressing the links between the countryside and national identity.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Relatório de Estágio apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão do Território, especialização em Detecção Remota e Sistemas de Informação Geográfica

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Abstract: Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Thesis submitted in fulfilment of the requirements for the Degree of Master of Science in Computer Science

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This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

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The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

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Field Lab of Entrepreneurial Innovative Ventures